SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Showing 62016225 of 10420 papers

TitleStatusHype
Incorporating Convolution Designs into Visual TransformersCode1
ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised LearningCode0
Hierarchical Representation based Query-Specific Prototypical Network for Few-Shot Image Classification0
Robust Models Are More Interpretable Because Attributions Look NormalCode1
Local Patch AutoAugment with Multi-Agent CollaborationCode1
Transfer learning for automatic brain tumor classification Using MRI Images.0
ThanosNet: A Novel Trash Classification Method Using MetadataCode0
Scalable Vision Transformers with Hierarchical PoolingCode1
Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image ClassificationCode1
Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and BenchmarkCode0
Variational Knowledge Distillation for Disease Classification in Chest X-Rays0
Implementation of Artificial Neural Networks for the Nepta-Uranian Interplanetary (NUIP) Mission0
ConViT: Improving Vision Transformers with Soft Convolutional Inductive BiasesCode0
3D Human Pose Estimation with Spatial and Temporal TransformersCode1
TrivialAugment: Tuning-free Yet State-of-the-Art Data AugmentationCode1
Stride and Translation Invariance in CNNs0
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark DatasetCode1
MSMatch: Semi-Supervised Multispectral Scene Classification with Few LabelsCode1
TPPI-Net: Towards Efficient and Practical Hyperspectral Image Classification0
Danish Fungi 2020 -- Not Just Another Image Recognition DatasetCode1
The Low-Rank Simplicity Bias in Deep NetworksCode1
Consistency-based Active Learning for Object DetectionCode1
Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation0
Triplet-Watershed for Hyperspectral Image ClassificationCode1
Large-Scale Zero-Shot Image Classification from Rich and Diverse Textual Descriptions0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified